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The Institute for Data, Econometrics, Algorithms, and Learning (IDEAL). Northwestern, TTIC, and UIC. Position ID: Northwestern-The Institute for Data, Econometrics, Algorithms, and Learning (IDEAL
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particular focus on applications relevant to the Arab world. The successful applicant will join a multidisciplinary research team working at the intersection of machine learning, algorithmic fairness, human
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research for understanding the learned algorithms in brains and machines. The post holder will provide guidance to less experienced members of the research group, including postdocs, research assistants
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algorithms where the agent can propose updates to its own world model structure, but these updates are only accepted after a formal verification step confirms that the new model still adheres to its core
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data for urban characterization. The work includes developing algorithms, performing large-scale analyses, and collaborating with partners across disciplines in remote sensing, urban studies, and climate
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, or the design of efficient, explainable, and scalable query engines. The successful applicant will help design and build novel systems and algorithms that challenge traditional assumptions in databases, guided by
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research team working at the intersection of machine learning, algorithmic fairness, human-computer interaction, and responsible AI. The project aims to investigate how bias emerges in data pipelines and AI
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conferences and journals. Overview: The successful candidate will join an interdisciplinary team focused on developing innovative numerical algorithms and software to address emerging challenges in scientific
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algorithms, ideally in the healthcare or mental health domain Desirable criteria Track record of successful research grant applications, or attempts to obtain grant funding. Previous development of ML-based
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space)? What are appropriate descriptors of spatial distribution in the field of materials science (e.g., Voronoi tessellations, particle-particle distances, etc.)? What are appropriate algorithms